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In this article we introduce a Python module named’ ASAHM’ (Automated Subtractive Additive Hybrid Manufacturing) that generates G-code files for hybrid FFF (Fused Filament Fabrication)/CNC (Computer Numerical Control) manufacturing, which can be used on multi-tool 3D printers from files generated by slicers such as Cura, Prusa Slicer, or Simplify3D. The module is based on the Trimesh library, which allows for common 3D mesh manipulations, and the Shapely library, used for the manipulation and analysis of 2D geometric shapes. By integrating contouring and surfacing operations that enable the machining of the entire 3D-printed geometries, ASAHM represents a first step towards the large-scale adoption of a hybrid FFF/CNC process.

In a previous publication, we presented CRAPPY, a Python module designed for researchers wishing to easily develop code for driving complex experimental setups. In a complemented version, now targeting a broader audience, we extended the framework to include low-cost sensors, actuators, and cameras. Using such devices, it is now possible to set up tests with CRAPPY in a more cost-effective and flexible way. This can be achieved from embedded computers like the Raspberry Pi, on which the module is now fully functional. Alternatively, we introduce a solution for driving embedded sensors and actuators directly from a regular PC. Other enhancements for the integration of microcontrollers and remote equipment are also described. Based on examples of existing tests driven using CRAPPY, we demonstrate in this paper the feasibility of including low-cost equipment in experimental setups to obtain relevant results.

Performing relevant mechanical tests requires complex experimental setups. CRAPPY is a Python module meant to help researchers develop code for systems involving several sensors and/or actuators. It features a number of advanced tools to perform measurements, drive hardware, and process data. CRAPPY aims at making the design of advanced tests easier and accessible to non-code experts. It is highly modular, and new devices can easily be added to the module as long as they can be interfaced with Python. Users can fully take advantage of Python’s versatility in their experimental scripts, as they are not constrained by any GUI. CRAPPY features a wide variety of tools specific to experimental mechanics as it was first developed for this field, but tools and instruments from other domains can as well be included within its framework. In this paper, the project and its functionalities will be described, illustrated by short examples of code and existing experimental setups using CRAPPY.